Applied Predictive Modeling- The package is an R companion to the Springer book "Applied Predictive Modeling". It contains several functions and data sets used in the text, as well as R scripts to re-create the analyses in each chapter.

Finite Mixure of AFT and FMR models- FMRS package provides estimation and variable selection in Finite Mixture of Accelerated Failure Time Regression (FMAFTR) and Finite Mixture of Regression (FMR) models with a large number of covariates and/or right censoring and heterogeneous structure.

Low Rank Gaussian Process Regression- Fit a Low Rank Gaussian Process Regression / Linear Mixed Model for large datasets. These models are widely used in statistical genetics as a test of association while correcting for the confounding effects of kinship and population structure.

Non-linear models in agriculture- This project is an R package to support a publication related to non-linear regression models in agriculture. The package contains some new selfStarter functions, data and documentation.

cusp- Package for applying Cobb's maximum likelihood method to fitting cusp catastrophe models to data. The package was published in the Journal of Statistical Software [see www.jstatsoft.org/v32/i08/paper].